ML Engineer- Alzheimer Drug Discovery Pre-Seed BioTech

Our client is a seed stage TechBio company building a platform solution for identifying drug targets for neurological diseases with in-vitro validation. The founders have track records building successful series C HealthTech, and have just raised £2m pre-seed stage funding last week. * This role is to join the business as employee No.3 along with other 5 first hires. * 5 days per week in Victoria House Soho London.

About the Role :

You will build and own the modelling layer at the core of company's target identification platform. Working with high-dimensional multi-omics data, you will develop predictive models that generate biological insights from complex datasets. This is a research-facing engineering role — you will work closely with bioinformaticians and software engineers, and your models will directly shape which targets reach the wet lab.

Responsibilities

• Build and validate predictive models on high-dimensional biological datasets
• Develop and maintain scalable ML pipelines from research prototype to production
• Design scoring and prioritisation frameworks integrating multiple evidence streams
• Collaborate closely with bioinformatics and engineering colleagues
• Contribute to reproducible, well-tested codebases

Requirements:

• Strong Python ML engineering: PyTorch, scikit-learn
• Experience with deep learning and sequence models applied to high-dimensional, sparse biological data
• Solid statistical foundations: mixed models, multiple testing, effect size estimation
• Familiarity with genomics or multi-omics data types (methylation arrays, RNA-seq, genotype data)
• Experience building and validating predictive models in research or applied settings
• Comfort with regularisation strategies for high-dimensional problems

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